# 尝试SAM模型
import numpy as np
import torch
import matplotlib.pyplot as plt
import cv2
from segment_anything import SamPredictor, sam_model_registry
import os
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"   # 一个粗暴的方法，解决库重复初始化问题

def show_mask(mask, ax, random_color=False):
    if random_color:
        color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0)
    else:
        color = np.array([30/255, 144/255, 255/255, 0.6])
    h, w = mask.shape[-2:]
    mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1)
    ax.imshow(mask_image)
    
def show_points(coords, labels, ax, marker_size=375):
    pos_points = coords[labels==1]
    neg_points = coords[labels==0]
    ax.scatter(pos_points[:, 0], pos_points[:, 1], color='green', marker='*', s=marker_size, edgecolor='white', linewidth=1.25)
    ax.scatter(neg_points[:, 0], neg_points[:, 1], color='red', marker='*', s=marker_size, edgecolor='white', linewidth=1.25)   
    
def show_box(box, ax):
    x0, y0 = box[0], box[1]
    w, h = box[2] - box[0], box[3] - box[1]
    ax.add_patch(plt.Rectangle((x0, y0), w, h, edgecolor='green', facecolor=(0,0,0,0), lw=2))  

sam_checkpoint = "../model/sam_vit_h_4b8939.pth"
sam_model_type = "vit_h"
sam_device = "cuda"

image = cv2.imread('../test_images/1.jpg')
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

# 创建SAM
sam = sam_model_registry[sam_model_type](checkpoint=sam_checkpoint)
sam.to(device=sam_device)
predictor = SamPredictor(sam)
predictor.set_image(image)

#masks, _, _ = predictor.predict()

plt.figure(figsize=(10,10))
plt.imshow(image)
plt.axis('on')
plt.show()  